Research on ontologies has been pursued as a solution to the difficult problem of knowledge sharing. Ontologies consist of a domain description which suits the needs of all systems to be integrated. Any agreed ontology, however, is not the end of the problems involved in knowledge sharing since how we represent knowledge is intimately linked to the inferences we expect to perform with it. Knowledge sharing cannot ignore the similarities and differences between the inference engines participating in the information exchange. We illustrate this issue via a case study on resource-sensitive knowledge-based systems and we show how these can efficiently share their knowledge using combinator logics.